Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/54408
Type of publication: research article
Type of publication (PDB): Straipsnis konferencijos medžiagoje Clarivate Analytics Web of Science ar/ir Scopus / Article in Clarivate Analytics Web of Science or Scopus DB conference proceedings (P1a)
Field of Science: Informatika / Informatics (N009)
Author(s): Tamošiūnaitė, Minija;Prackevičienė, Erinija
Title: Application of the biologically inspired network for electroencephalogram analysis
Is part of: Computational intelligence : theory and applications international conference, 7th Fuzzy Days Dortmund, Germany, October 1–3, 2001 : proceedings. Berlin, Heidelberg : Springer, 2001
Extent: p. 18-27
Date: 2001
Series/Report no.: (Lecture Notes in Computer Science. Vol. 2206 0302-9743)
Keywords: Automatic seizure detection;Artificial neural network;Combining classifiers;Mental tasks
ISBN: 9783540427322
Abstract: Architecture of a neural network combining automatic feature extraction with the minimized amount of network training acquired by means of employing of a multistage training procedure is investigated. The network selects prototypical signals and calculates features based on the similarity of a signal to prototypes. The similarity is measured by the prognosis error of the linear regression model. The network is applied for the meaningful paroxysmal activity vs. background classification task and provides better accuracy than the methods using manually selected features. Performance of several modifications of the new architecture is being evaluated
Internet: https://doi.org/10.1007/3-540-45493-4_4
Affiliation(s): Kauno technologijos universitetas
Taikomosios informatikos katedra
Vytauto Didžiojo universitetas
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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